R: Functions to Facilitate the Simulation of Large Scale Assessment Data

# Functions to Facilitate the Simulation of Large Scale Assessment Data

## Documentation for package ‘lsasim’ version 2.1.6

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

lsasim-package | lsasim: A package for simulating large scale assessment data
.onAttach | Prints welcome message on package load
anova.lsasimcluster | Generate an ANOVA table for LSASIM clusters
attribute_cluster_labels | Attribute Labels in Hierarchical Structure
beta_gen | Generate regression coefficients
block_design | Assignment of test items to blocks
booklet_design | Assignment of item blocks to test booklets
booklet_sample | Assignment of test booklets to test takers
brr | Generate replicates of a dataset using Balanced Repeated Replication
calc_n_tilde | Calculate ñ
calc_replicate_weights | Calculate replicate weights and summary statistics
calc_se_rho | Calculate Standard Error of Intraclass Correlation
calc_var_between | Calculate variance between classes
calc_var_tot | Calculate the total variance
calc_var_within | Calculate variance within classes
check_condition | Check if an error condition is satisfied
check_ignored_parameters | Checks if provided parameters are ignored
check_n_N_class | Check class of n or N
check_valid_structure | Check if List is Valid
cluster_gen | Generate cluster sample
cluster_gen_separate | Generate cluster samples with individual questionnaires
cluster_gen_together | Generate cluster samples with lowest-level questionnaires
cluster_message | Print messages about clusters
convert_vector_to_list | Convert Vector to Expanded List
cor_gen | Generation of random correlation matrix
cov_gen | Generation of covariance matrices
cov_yfz_gen | Generate latent regression covariance matrix
cov_yxw_gen | Setup full YXW covariance matrix
cov_yxz_gen | Generate analytical covariance matrix
customize_summary | Customize Summary
draw_cluster_structure | Draw Cluster Structure
gen_cat_prop | Generates cat_prop for questionnaire_gen
gen_variable_n | Randomly generate the quantity of background variables
gen_X_W_cluster | Generate n_X and n_W for clusters
intraclass_cor | Intraclass correlation
irt_gen | Simulate item responses from an item response model
item_gen | Generation of item parameters from uniform distributions
jackknife | Generate replicates of a dataset using Jackknife
label_respondents | Label respondents
lambda_gen | Randomly generate a matrix of factor loadings
lsasim | lsasim: A package for simulating large scale assessment data
pisa2012_math_block | PISA 2012 mathematics item - item block indicator matrix
pisa2012_math_booklet | PISA 2012 mathematics item block - test booklet indicator matrix
pisa2012_math_item | Item parameter estimates for 2012 PISA mathematics assessment
pisa2012_q_cormat | Correlation matrix from the PISA 2012 background questionnaire
pisa2012_q_marginal | Marginal proportions from the PISA 2012 background questionnaire
pluralize | Pluralize words
print_anova | Print the ANOVA table
proportion_gen | Generation of random cumulative proportions
pt_bis_conversion | Analytical point-biserial conversion
questionnaire_gen | Generation of ordinal and continuous variables
questionnaire_gen_family | Generation of ordinal and continuous variables
questionnaire_gen_polychoric | Generation of ordinal and continuous variables
ranges | Defines vector as range
recalc_final_weights | Recalculate final weights
replicate_var | Sampling variance of the mean for replications
response_gen | Generation of item response data using a rotated block design
rzeropois | Generate data from a Zero-truncated Poisson
sample_from | Sample from population structure
sample_within_range | Sample from range
select | Transform regular vector into selection vector
split_cat_prop | Split variables in cat_prop
summary.lsasimcluster | Summarizes clusters
summary_2 | Dataset summary statistics
trim_sample | Trim sample
validate_questionnaire_gen | Wrapper-functions for check_condition
weight_responses | Weight responses
whitelist_message | Whitelist message